diff --git a/rag/folderinfo.py b/rag/folderinfo.py
index ff31f44..8cf3d99 100644
--- a/rag/folderinfo.py
+++ b/rag/folderinfo.py
@@ -216,358 +216,4 @@ where a.orgid = b.orgid
 			"message": f"处理 {len(recs)} 个文件，成功删除 {sum(1 for r in results if r['status'] == 'success')} 个",
 			"status_code": 200 if all(r["status"] == "success" for r in results) else 207
 		}
-	# async def get_doucment_chunks(self, realpath, timings):
-	# 	"""加载文件并进行文本分片"""
-	# 	debug(f"加载文件: {realpath}")
-	# 	start_load = time.time()
-	# 	supported_formats = File2Text.supported_types()
-	# 	debug(f"支持的文件格式:{supported_formats}")
-	# 	ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else ''
-	# 	if ext not in supported_formats:
-	# 		raise ValueError(f"不支持的文件格式: {ext}, 支持的格式: {', '.join(supported_formats)}")
-	# 	text = fileloader(realpath)
-	# 	text = re.sub(r'[^\u4e00-\u9fa5a-zA-Z0-9\s.;,\n/]', '', text)
-	# 	timings["load_file"] = time.time() - start_load
-	# 	debug(f"加载文件耗时: {timings['load_file']:.2f} 秒, 文本长度: {len(text)}")
-	#
-	# 	if not text or not text.strip():
-	# 		raise ValueError(f"文件 {realpath} 加载为空")
-	#
-	# 	document = Document(page_content=text)
-	# 	text_splitter = RecursiveCharacterTextSplitter(
-	# 		chunk_size=500,
-	# 		chunk_overlap=100,
-	# 		length_function=len
-	# 	)
-	# 	debug("开始分片文件内容")
-	# 	start_split = time.time()
-	# 	chunks = text_splitter.split_documents([document])
-	# 	timings["split_text"] = time.time() - start_split
-	# 	debug(f"文本分片耗时: {timings['split_text']:.2f} 秒, 分片数量: {len(chunks)}")
-	#
-	# 	if not chunks:
-	# 		raise ValueError(f"文件 {realpath} 未生成任何文档块")
-	#
-	# 	return chunks
-	#
-	# async def docs_embedding(self, request, chunks, service_params, userid, timings):
-	# 	"""调用嵌入服务生成向量"""
-	# 	debug("调用嵌入服务生成向量")
-	# 	start_embedding = time.time()
-	# 	texts = [chunk.page_content for chunk in chunks]
-	# 	embeddings = []
-	# 	for i in range(0, len(texts), 10):
-	# 		batch_texts = texts[i:i + 10]
-	# 		batch_embeddings = await APIService().get_embeddings(
-	# 			request=request,
-	# 			texts=batch_texts,
-	# 			upappid=service_params['embedding'],
-	# 			apiname="BAAI/bge-m3",
-	# 			user=userid
-	# 		)
-	# 		embeddings.extend(batch_embeddings)
-	#
-	# 	if not embeddings or not all(len(vec) == 1024 for vec in embeddings):
-	# 		raise ValueError("所有嵌入向量必须是长度为 1024 的浮点数列表")
-	#
-	# 	timings["generate_embeddings"] = time.time() - start_embedding
-	# 	debug(f"生成嵌入向量耗时: {timings['generate_embeddings']:.2f} 秒, 嵌入数量: {len(embeddings)}")
-	# 	return embeddings
-	#
-	# async def embedding_2_vdb(self, request, chunks, embeddings, realpath, orgid, fiid, id, service_params, userid,
-	# 						  db_type, timings):
-	# 	"""准备数据并插入 Milvus"""
-	# 	debug(f"准备数据并调用插入文件端点: {realpath}")
-	# 	filename = os.path.basename(realpath).rsplit('.', 1)[0]
-	# 	ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else ''
-	# 	upload_time = datetime.now().isoformat()
-	#
-	# 	chunks_data = [
-	# 		{
-	# 			"userid": orgid,
-	# 			"knowledge_base_id": fiid,
-	# 			"text": chunk.page_content,
-	# 			"vector": embeddings[i],
-	# 			"document_id": id,
-	# 			"filename": filename + '.' + ext,
-	# 			"file_path": realpath,
-	# 			"upload_time": upload_time,
-	# 			"file_type": ext,
-	# 		}
-	# 		for i, chunk in enumerate(chunks)
-	# 	]
-	#
-	# 	start_milvus = time.time()
-	# 	for i in range(0, len(chunks_data), 10):
-	# 		batch_chunks = chunks_data[i:i + 10]
-	# 		result = await APIService().milvus_insert_document(
-	# 			request=request,
-	# 			chunks=batch_chunks,
-	# 			db_type=db_type,
-	# 			upappid=service_params['vdb'],
-	# 			apiname="milvus/insertdocument",
-	# 			user=userid
-	# 		)
-	# 		if result.get("status") != "success":
-	# 			raise ValueError(result.get("message", "Milvus 插入失败"))
-	#
-	# 	timings["insert_milvus"] = time.time() - start_milvus
-	# 	debug(f"Milvus 插入耗时: {timings['insert_milvus']:.2f} 秒")
-	# 	return chunks_data
-	#
-	# async def get_triples(self, request, chunks, service_params, userid, timings):
-	# 	"""调用三元组抽取服务"""
-	# 	debug("调用三元组抽取服务")
-	# 	start_triples = time.time()
-	# 	chunk_texts = [doc.page_content for doc in chunks]
-	# 	triples = []
-	# 	for i, chunk in enumerate(chunk_texts):
-	# 		result = await APIService().extract_triples(
-	# 			request=request,
-	# 			text=chunk,
-	# 			upappid=service_params['triples'],
-	# 			apiname="Babelscape/mrebel-large",
-	# 			user=userid
-	# 		)
-	# 		if isinstance(result, list):
-	# 			triples.extend(result)
-	# 			debug(f"分片 {i + 1} 抽取到 {len(result)} 个三元组")
-	# 		else:
-	# 			error(f"分片 {i + 1} 处理失败: {str(result)}")
-	#
-	# 	unique_triples = []
-	# 	seen = set()
-	# 	for t in triples:
-	# 		identifier = (t['head'].lower(), t['tail'].lower(), t['type'].lower())
-	# 		if identifier not in seen:
-	# 			seen.add(identifier)
-	# 			unique_triples.append(t)
-	# 		else:
-	# 			for existing in unique_triples:
-	# 				if (existing['head'].lower() == t['head'].lower() and
-	# 						existing['tail'].lower() == t['tail'].lower() and
-	# 						len(t['type']) > len(existing['type'])):
-	# 					unique_triples.remove(existing)
-	# 					unique_triples.append(t)
-	# 					debug(f"替换三元组为更具体类型: {t}")
-	# 					break
-	#
-	# 	timings["extract_triples"] = time.time() - start_triples
-	# 	debug(f"三元组抽取耗时: {timings['extract_triples']:.2f} 秒, 抽取到 {len(unique_triples)} 个三元组")
-	# 	return unique_triples
-	#
-	# async def triple2graphdb(self, request, unique_triples, id, fiid, orgid, service_params, userid, timings):
-	# 	"""调用 Neo4j 插入三元组"""
-	# 	debug(f"插入 {len(unique_triples)} 个三元组到 Neo4j")
-	# 	start_neo4j = time.time()
-	# 	if unique_triples:
-	# 		for i in range(0, len(unique_triples), 30):
-	# 			batch_triples = unique_triples[i:i + 30]
-	# 			neo4j_result = await APIService().neo4j_insert_triples(
-	# 				request=request,
-	# 				triples=batch_triples,
-	# 				document_id=id,
-	# 				knowledge_base_id=fiid,
-	# 				userid=orgid,
-	# 				upappid=service_params['gdb'],
-	# 				apiname="neo4j/inserttriples",
-	# 				user=userid
-	# 			)
-	# 			if neo4j_result.get("status") != "success":
-	# 				raise ValueError(f"Neo4j 三元组插入失败: {neo4j_result.get('message', '未知错误')}")
-	# 			info(f"文件三元组成功插入 Neo4j: {neo4j_result.get('message')}")
-	# 		timings["insert_neo4j"] = time.time() - start_neo4j
-	# 		debug(f"Neo4j 插入耗时: {timings['insert_neo4j']:.2f} 秒")
-	# 	else:
-	# 		debug("未抽取到三元组")
-	# 		timings["insert_neo4j"] = 0.0
-	#
-	# async def delete_from_milvus(self, request, orgid, realpath, fiid, id, service_params, userid, db_type):
-	# 	"""调用 Milvus 删除文档"""
-	# 	debug(f"调用删除文件端点: userid={orgid}, file_path={realpath}, knowledge_base_id={fiid}, document_id={id}")
-	# 	milvus_result = await APIService().milvus_delete_document(
-	# 		request=request,
-	# 		userid=orgid,
-	# 		file_path=realpath,
-	# 		knowledge_base_id=fiid,
-	# 		document_id=id,
-	# 		db_type=db_type,
-	# 		upappid=service_params['vdb'],
-	# 		apiname="milvus/deletedocument",
-	# 		user=userid
-	# 	)
-	# 	if milvus_result.get("status") != "success":
-	# 		raise ValueError(milvus_result.get("message", "Milvus 删除失败"))
-	#
-	# async def delete_from_neo4j(self, request, id, service_params, userid):
-	# 	"""调用 Neo4j 删除文档"""
-	# 	debug(f"调用 Neo4j 删除文档端点: document_id={id}")
-	# 	neo4j_result = await APIService().neo4j_delete_document(
-	# 		request=request,
-	# 		document_id=id,
-	# 		upappid=service_params['gdb'],
-	# 		apiname="neo4j/deletedocument",
-	# 		user=userid
-	# 	)
-	# 	if neo4j_result.get("status") != "success":
-	# 		raise ValueError(neo4j_result.get("message", "Neo4j 删除失败"))
-	# 	nodes_deleted = neo4j_result.get("nodes_deleted", 0)
-	# 	rels_deleted = neo4j_result.get("rels_deleted", 0)
-	# 	info(f"成功删除 document_id={id} 的 {nodes_deleted} 个 Neo4j 节点和 {rels_deleted} 个关系")
-	# 	return nodes_deleted, rels_deleted
-
-	# async def file_uploaded(self, request, ns, userid):
-	# 	"""将文档插入 Milvus 并抽取三元组到 Neo4j"""
-	# 	debug(f'Received ns: {ns=}')
-	# 	env = request._run_ns
-	# 	realpath = ns.get('realpath', '')
-	# 	fiid = ns.get('fiid', '')
-	# 	id = ns.get('id', '')
-	# 	orgid = ns.get('ownerid', '')
-	# 	db_type = ''
-	#
-	# 	debug(f'Inserting document: file_path={realpath}, userid={orgid}, db_type={db_type}, knowledge_base_id={fiid}, document_id={id}')
-	#
-	# 	timings = {}
-	# 	start_total = time.time()
-	#
-	# 	try:
-	# 		if not orgid or not fiid or not id:
-	# 			raise ValueError("orgid、fiid 和 id 不能为空")
-	# 		if len(orgid) > 32 or len(fiid) > 255:
-	# 			raise ValueError("orgid 或 fiid 的长度超出限制")
-	# 		if not os.path.exists(realpath):
-	# 			raise ValueError(f"文件 {realpath} 不存在")
-	#
-	# 		# 获取服务参数
-	# 		service_params = await get_service_params(orgid)
-	# 		if not service_params:
-	# 			raise ValueError("无法获取服务参数")
-	#
-	# 		chunks = await self.get_doucment_chunks(realpath, timings)
-	# 		embeddings = await self.docs_embedding(request, chunks, service_params, userid, timings)
-	# 		await self.embedding_2_vdb(request, chunks, embeddings, realpath, orgid, fiid, id, service_params, userid,db_type, timings)
-	# 		triples = await self.get_triples(request, chunks, service_params, userid, timings)
-	# 		await self.triple2graphdb(request, triples, id, fiid, orgid, service_params, userid, timings)
-	#
-	# 		timings["total"] = time.time() - start_total
-	# 		debug(f"总耗时: {timings['total']:.2f} 秒")
-	# 		return {
-	# 			"status": "success",
-	# 			"userid": orgid,
-	# 			"document_id": id,
-	# 			"collection_name": "ragdb",
-	# 			"timings": timings,
-	# 			"unique_triples": triples,
-	# 			"message": f"文件 {realpath} 成功嵌入并处理三元组",
-	# 			"status_code": 200
-	# 		}
-	# 	except Exception as e:
-	# 		error(f"插入文档失败: {str(e)}, 堆栈: {traceback.format_exc()}")
-	# 		timings["total"] = time.time() - start_total
-	# 		return {
-	# 			"status": "error",
-	# 			"document_id": id,
-	# 			"collection_name": "ragdb",
-	# 			"timings": timings,
-	# 			"message": f"插入文档失败: {str(e)}",
-	# 			"status_code": 400
-	# 		}
-	#
-	# async def file_deleted(self, request, recs, userid):
-	# 	"""删除用户指定文件数据，包括 Milvus 和 Neo4j 中的记录"""
-	# 	if not isinstance(recs, list):
-	# 		recs = [recs]
-	# 	results = []
-	# 	total_nodes_deleted = 0
-	# 	total_rels_deleted = 0
-	#
-	# 	for rec in recs:
-	# 		id = rec.get('id', '')
-	# 		realpath = rec.get('realpath', '')
-	# 		fiid = rec.get('fiid', '')
-	# 		orgid = rec.get('ownerid', '')
-	# 		db_type = ''
-	# 		collection_name = "ragdb" if not db_type else f"ragdb_{db_type}"
-	#
-	# 		try:
-	# 			required_fields = ['id', 'realpath', 'fiid', 'ownerid']
-	# 			missing_fields = [field for field in required_fields if not rec.get(field, '')]
-	# 			if missing_fields:
-	# 				raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}")
-	#
-	# 			service_params = await get_service_params(orgid)
-	# 			if not service_params:
-	# 				raise ValueError("无法获取服务参数")
-	#
-	# 			# 调用 Milvus 删除
-	# 			await self.delete_from_milvus(request, orgid, realpath, fiid, id, service_params, userid, db_type)
-	#
-	# 			# 调用 Neo4j 删除
-	# 			neo4j_deleted_nodes = 0
-	# 			neo4j_deleted_rels = 0
-	# 			try:
-	# 				nodes_deleted, rels_deleted = await self.delete_from_neo4j(request, id, service_params, userid)
-	# 				neo4j_deleted_nodes += nodes_deleted
-	# 				neo4j_deleted_rels += rels_deleted
-	# 				total_nodes_deleted += nodes_deleted
-	# 				total_rels_deleted += rels_deleted
-	# 			except Exception as e:
-	# 				error(f"删除 document_id={id} 的 Neo4j 数据失败: {str(e)}")
-	#
-	# 			results.append({
-	# 				"status": "success",
-	# 				"collection_name": collection_name,
-	# 				"document_id": id,
-	# 				"message": f"成功删除文件 {realpath} 的 Milvus 记录，{neo4j_deleted_nodes} 个 Neo4j 节点，{neo4j_deleted_rels} 个 Neo4j 关系",
-	# 				"status_code": 200
-	# 			})
-	#
-	# 		except Exception as e:
-	# 			error(f"删除文档 {realpath} 失败: {str(e)}, 堆栈: {traceback.format_exc()}")
-	# 			results.append({
-	# 				"status": "error",
-	# 				"collection_name": collection_name,
-	# 				"document_id": id,
-	# 				"message": f"删除文档 {realpath} 失败: {str(e)}",
-	# 				"status_code": 400
-	# 			})
-	#
-	# 	return {
-	# 		"status": "success" if all(r["status"] == "success" for r in results) else "partial",
-	# 		"results": results,
-	# 		"total_nodes_deleted": total_nodes_deleted,
-	# 		"total_rels_deleted": total_rels_deleted,
-	# 		"message": f"处理 {len(recs)} 个文件，成功删除 {sum(1 for r in results if r['status'] == 'success')} 个",
-	# 		"status_code": 200 if all(r["status"] == "success" for r in results) else 207
-	# 	}
-
-
-# async def test_ragfilemgr():
-# 	"""测试 RagFileMgr 类的 get_service_params"""
-# 	print("初始化数据库连接池...")
-# 	dbs = {
-# 		"kyrag": {
-# 			"driver": "aiomysql",
-# 			"async_mode": True,
-# 			"coding": "utf8",
-# 			"maxconn": 100,
-# 			"dbname": "kyrag",
-# 			"kwargs": {
-# 				"user": "test",
-# 				"db": "kyrag",
-# 				"password": "QUZVcXg5V1p1STMybG5Ia6mX9D0v7+g=",
-# 				"host": "db"
-# 			}
-# 		}
-# 	}
-# 	DBPools(dbs)
-#
-# 	ragfilemgr = RagFileMgr()
-# 	orgid = "04J6VbxLqB_9RPMcgOv_8"
-# 	result = await get_service_params(orgid)
-# 	print(f"get_service_params 结果: {result}")
-#
-#
-# if __name__ == "__main__":
-# 	asyncio.run(test_ragfilemgr())
+